Various devices exist for sensing biological data from a patient. This sensed biological data can relate to any aspect of a patient's condition such as body temperature, respiration, activity, blood chemistry, electrical heart activity, etc. The sensed biological data is sensed in a particular context (i.e., from a particular patient by a particular device). Knowing information about the context enhances the diagnostic value of the sensed biological data. Supporting data relates to the particular context in which the sensed biological data is obtained. For instance consider a scenario involving an implantable medical device (IMD) employed to sense biological data related to heart function from an individual patient. Clinical data regarding the individual patient, such as the patient's age and the patient's sex, can contribute to the context. IMDs can sense large amounts of biological data relating to heart function, patient activity, thoracic impedance, etc. One aspect of heart function can be sensed as intracardiac electrogram (IEGM) data. The IEGM data is sensed with sensors that are adjusted for various settings or parameters such as sensitivity, amplification and filter characteristics. Further, the sensed biological data may be delivered from the sensor to the IMD which may further process the data, such as by an analog-to-digital conversion, according to its own internal settings. The settings of the sensor and/or the IMD can contribute to the context of the sensed biological data.
Often, some or all of the sensed biological data is subsequently downloaded from the patient and analyzed to diagnose a patient condition(s). Knowing the context in which the biological data was sensed can enhance the diagnostic value of the sensed biological data. For instance, a sensitivity setting on the IMD will affect whether a P-wave recorded in the IEGM data is actually a P-wave or some other cardiac event, such as a ventricular event.
Presently only rudimentary techniques are employed to associate context with the biological data. For instance, when biological data is downloaded from an IMD, extra process steps can be taken to also download at least some supporting data in a separate process. A clinician can create a data table to cross-reference the biological data and the supporting data. The clinician can enter and save the supporting data and cross-reference the supporting data to the biological data utilizing the data table. These techniques rely on human involvement to complete the data table and enter the supporting data, which may be accomplished on only a limited scale or not at all. Further, the data table and/or the supporting data may be lost at some point. In some cases, other clinicians accessing the sensed biological data may not know of the existence of the data table and/or the supporting data and/or the clinicians may be unable to locate the data tables and/or the supporting data. Often, the end result is that the context of the biological data is effectively unknown or only partially known. Improved techniques for associating biological data with its contextual supporting data could improve patient care at a micro-level and forward research knowledge at a macro-level.